Overview

Dataset statistics

Number of variables19
Number of observations2415
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory360.8 KiB
Average record size in memory153.0 B

Variable types

DateTime1
TimeSeries15
Boolean1
Numeric2

Timeseries statistics

Number of series15
Time series length2415
Starting point2010-01-26 00:00:00
Ending point2019-08-30 00:00:00
Period1 day, 10 hours and 49 minutes
2026-02-06T03:47:39.985219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:40.676482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

repaired? has constant value "False"Constant
AD is highly overall correlated with OBVHigh correlation
ATR is highly overall correlated with TRANGEHigh correlation
CMO is highly overall correlated with MFI and 2 other fieldsHigh correlation
EMA is highly overall correlated with KAMA and 6 other fieldsHigh correlation
KAMA is highly overall correlated with EMA and 6 other fieldsHigh correlation
MA is highly overall correlated with EMA and 6 other fieldsHigh correlation
MFI is highly overall correlated with CMO and 2 other fieldsHigh correlation
MidPrice is highly overall correlated with EMA and 6 other fieldsHigh correlation
NATR is highly overall correlated with EMA and 7 other fieldsHigh correlation
OBV is highly overall correlated with AD and 1 other fieldsHigh correlation
ROC is highly overall correlated with CMO and 2 other fieldsHigh correlation
TRANGE is highly overall correlated with ATRHigh correlation
TSF is highly overall correlated with EMA and 6 other fieldsHigh correlation
WILLR is highly overall correlated with CMO and 2 other fieldsHigh correlation
WMA is highly overall correlated with EMA and 6 other fieldsHigh correlation
close is highly overall correlated with EMA and 6 other fieldsHigh correlation
close is non stationaryNon stationary
MA is non stationaryNon stationary
EMA is non stationaryNon stationary
KAMA is non stationaryNon stationary
WMA is non stationaryNon stationary
MidPrice is non stationaryNon stationary
AD is non stationaryNon stationary
OBV is non stationaryNon stationary
NATR is non stationaryNon stationary
TSF is non stationaryNon stationary
close is seasonalSeasonal
MA is seasonalSeasonal
EMA is seasonalSeasonal
KAMA is seasonalSeasonal
WMA is seasonalSeasonal
MidPrice is seasonalSeasonal
AD is seasonalSeasonal
OBV is seasonalSeasonal
NATR is seasonalSeasonal
Date has unique valuesUnique
EMA has unique valuesUnique
KAMA has unique valuesUnique
WMA has unique valuesUnique
MFI has unique valuesUnique
ROC has unique valuesUnique
NATR has unique valuesUnique
ATR has unique valuesUnique
TSF has unique valuesUnique

Reproduction

Analysis started2026-02-06 03:47:10.882494
Analysis finished2026-02-06 03:47:39.724620
Duration28.84 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
Minimum2010-01-26 00:00:00
Maximum2019-08-30 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-06T03:47:40.931348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:41.053920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2046
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.009536
Minimum26.209999
Maximum113.93
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:41.212936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.209999
5-th percentile42.097999
Q151.92
median73.449997
Q393.959999
95-th percentile104.727
Maximum113.93
Range87.720001
Interquartile range (IQR)42.039999

Descriptive statistics

Standard deviation22.136196
Coefficient of variation (CV)0.30319595
Kurtosis-1.3944377
Mean73.009536
Median Absolute Deviation (MAD)21.039997
Skewness-0.021273181
Sum176318.03
Variance490.01116
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6227996788
2026-02-06T03:47:41.355894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:41.729254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:42.723232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
44.659999856
 
0.2%
53.900001534
 
0.2%
93.959999084
 
0.2%
52.139999393
 
0.1%
81.253
 
0.1%
45.880001073
 
0.1%
55.259998323
 
0.1%
97.010002143
 
0.1%
103.30999763
 
0.1%
47.639999393
 
0.1%
Other values (2036)2380
98.6%
ValueCountFrequency (%)
26.209999081
< 0.1%
26.549999241
< 0.1%
27.450000761
< 0.1%
27.940000531
< 0.1%
28.459999081
< 0.1%
29.040000921
< 0.1%
29.420000081
< 0.1%
29.440000531
< 0.1%
29.530000691
< 0.1%
29.639999391
< 0.1%
ValueCountFrequency (%)
113.93000031
< 0.1%
113.51999661
< 0.1%
112.86000061
< 0.1%
112.79000091
< 0.1%
112.76000211
< 0.1%
112.29000091
< 0.1%
112.27999881
< 0.1%
112.20999911
< 0.1%
111.44999691
< 0.1%
111.05000311
< 0.1%
2026-02-06T03:47:41.486617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

repaired?
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.2 KiB
False
2415 
ValueCountFrequency (%)
False2415
100.0%
2026-02-06T03:47:43.372315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

MA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2393
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.049663
Minimum29.173
Maximum112.159
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:43.474509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.173
5-th percentile42.0861
Q151.835001
median73.592999
Q394.232999
95-th percentile104.7409
Maximum112.159
Range82.985999
Interquartile range (IQR)42.397998

Descriptive statistics

Standard deviation22.059307
Coefficient of variation (CV)0.30197685
Kurtosis-1.4067001
Mean73.049663
Median Absolute Deviation (MAD)21.168002
Skewness-0.029277992
Sum176414.93
Variance486.61302
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4790529807
2026-02-06T03:47:43.602133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:43.957237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:45.257876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
74.743999482
 
0.1%
99.216000372
 
0.1%
46.659999852
 
0.1%
47.597000122
 
0.1%
53.038000112
 
0.1%
93.922998812
 
0.1%
96.27300112
 
0.1%
88.816000372
 
0.1%
64.327000432
 
0.1%
49.047999952
 
0.1%
Other values (2383)2395
99.2%
ValueCountFrequency (%)
29.173000141
< 0.1%
29.232000161
< 0.1%
29.381000141
< 0.1%
29.450000191
< 0.1%
29.45399991
< 0.1%
29.531999971
< 0.1%
29.711999891
< 0.1%
29.871000291
< 0.1%
30.001999861
< 0.1%
30.005999951
< 0.1%
ValueCountFrequency (%)
112.15899961
< 0.1%
112.051
< 0.1%
111.6571
< 0.1%
111.27100071
< 0.1%
110.99400021
< 0.1%
110.68900071
< 0.1%
110.11400071
< 0.1%
109.48300021
< 0.1%
109.46300051
< 0.1%
109.28500061
< 0.1%
2026-02-06T03:47:43.723183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

EMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.051763
Minimum29.287779
Maximum111.98617
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:45.983070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.287779
5-th percentile42.332275
Q151.792681
median73.663575
Q394.327588
95-th percentile104.58309
Maximum111.98617
Range82.698395
Interquartile range (IQR)42.534907

Descriptive statistics

Standard deviation22.02642
Coefficient of variation (CV)0.30151798
Kurtosis-1.4133331
Mean73.051763
Median Absolute Deviation (MAD)21.132357
Skewness-0.030759268
Sum176420.01
Variance485.16317
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5889330355
2026-02-06T03:47:46.114104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:46.474544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:47.447619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
77.385473811
 
< 0.1%
76.709932791
 
< 0.1%
76.151763081
 
< 0.1%
75.558715141
 
< 0.1%
75.353494261
 
< 0.1%
75.694677731
 
< 0.1%
75.92837331
 
< 0.1%
75.421396221
 
< 0.1%
74.65205191
 
< 0.1%
74.149860531
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
29.287778661
< 0.1%
29.321249231
< 0.1%
29.342840381
< 0.1%
29.537273421
< 0.1%
29.739331751
< 0.1%
29.761405611
< 0.1%
30.012638151
< 0.1%
30.05581681
< 0.1%
30.385668451
< 0.1%
30.422970081
< 0.1%
ValueCountFrequency (%)
111.98617381
< 0.1%
111.81596091
< 0.1%
111.64532431
< 0.1%
111.3476041
< 0.1%
111.13761851
< 0.1%
110.75486691
< 0.1%
110.30928131
< 0.1%
109.88689961
< 0.1%
109.35509981
< 0.1%
109.24804021
< 0.1%
2026-02-06T03:47:46.239788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

KAMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.828771
Minimum28.98641
Maximum110.50473
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:48.185719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28.98641
5-th percentile41.896237
Q151.587049
median73.307337
Q394.661749
95-th percentile105.10058
Maximum110.50473
Range81.51832
Interquartile range (IQR)43.0747

Descriptive statistics

Standard deviation22.153973
Coefficient of variation (CV)0.3041926
Kurtosis-1.3982525
Mean72.828771
Median Absolute Deviation (MAD)21.466267
Skewness-0.022778722
Sum175881.48
Variance490.79852
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5696771131
2026-02-06T03:47:48.332733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:48.709584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:50.056815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
75.949905411
 
< 0.1%
75.448458091
 
< 0.1%
75.088957031
 
< 0.1%
74.630312671
 
< 0.1%
74.614973391
 
< 0.1%
74.677811881
 
< 0.1%
74.700986781
 
< 0.1%
74.638504111
 
< 0.1%
74.480175851
 
< 0.1%
74.360010621
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
28.986409871
< 0.1%
29.009892931
< 0.1%
29.01083371
< 0.1%
29.026915391
< 0.1%
29.063092761
< 0.1%
29.079548131
< 0.1%
29.099787661
< 0.1%
29.113922431
< 0.1%
29.148627321
< 0.1%
29.181849841
< 0.1%
ValueCountFrequency (%)
110.50473021
< 0.1%
110.48456821
< 0.1%
110.44889861
< 0.1%
110.14778191
< 0.1%
109.50401991
< 0.1%
108.9391511
< 0.1%
108.21942441
< 0.1%
108.11824781
< 0.1%
108.09014681
< 0.1%
108.02457861
< 0.1%
2026-02-06T03:47:48.464603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.035537
Minimum28.844364
Maximum112.62473
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:50.785944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28.844364
5-th percentile42.107236
Q151.825637
median73.469274
Q394.187545
95-th percentile104.78122
Maximum112.62473
Range83.780363
Interquartile range (IQR)42.361908

Descriptive statistics

Standard deviation22.074215
Coefficient of variation (CV)0.30223937
Kurtosis-1.4051794
Mean73.035537
Median Absolute Deviation (MAD)21.169819
Skewness-0.027085083
Sum176380.82
Variance487.27096
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5614110111
2026-02-06T03:47:50.916049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:51.295937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:52.300004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
76.443636951
 
< 0.1%
75.746181971
 
< 0.1%
75.172727271
 
< 0.1%
74.57218171
 
< 0.1%
74.369818121
 
< 0.1%
74.741455081
 
< 0.1%
75.100182831
 
< 0.1%
74.772364391
 
< 0.1%
74.143455641
 
< 0.1%
73.702728131
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
28.844363821
< 0.1%
28.966545451
< 0.1%
29.063636541
< 0.1%
29.091999851
< 0.1%
29.288727531
< 0.1%
29.335818311
< 0.1%
29.509999951
< 0.1%
29.747454381
< 0.1%
29.755272741
< 0.1%
29.836908791
< 0.1%
ValueCountFrequency (%)
112.62472691
< 0.1%
112.51436381
< 0.1%
112.21581851
< 0.1%
112.00345431
< 0.1%
111.62654591
< 0.1%
111.12727311
< 0.1%
110.52781831
< 0.1%
109.98672761
< 0.1%
109.7563641
< 0.1%
109.44218251
< 0.1%
2026-02-06T03:47:51.037513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MidPrice
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1493
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.944271
Minimum29.049999
Maximum111.395
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:53.021644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.049999
5-th percentile42.1605
Q151.869999
median73.43
Q394.232498
95-th percentile104.73
Maximum111.395
Range82.345001
Interquartile range (IQR)42.362499

Descriptive statistics

Standard deviation21.995321
Coefficient of variation (CV)0.30153596
Kurtosis-1.4053975
Mean72.944271
Median Absolute Deviation (MAD)21.189999
Skewness-0.027112513
Sum176160.41
Variance483.79415
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5213585116
2026-02-06T03:47:53.154755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:53.510266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:54.854246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
88.974998479
 
0.4%
59.325000769
 
0.4%
48.185001378
 
0.3%
73.770000468
 
0.3%
86.635002147
 
0.3%
48.910001757
 
0.3%
94.619998937
 
0.3%
52.780000697
 
0.3%
69.130001077
 
0.3%
41.225000387
 
0.3%
Other values (1483)2339
96.9%
ValueCountFrequency (%)
29.049999241
 
< 0.1%
29.251
 
< 0.1%
29.465001111
 
< 0.1%
29.515000341
 
< 0.1%
29.695000651
 
< 0.1%
29.789999013
0.1%
29.824998863
0.1%
30.114999771
 
< 0.1%
30.225000381
 
< 0.1%
30.265000342
0.1%
ValueCountFrequency (%)
111.39500051
 
< 0.1%
110.16500092
 
0.1%
109.84000021
 
< 0.1%
109.73500061
 
< 0.1%
109.39500053
0.1%
109.38499836
0.2%
108.79000091
 
< 0.1%
108.45000081
 
< 0.1%
108.22499854
0.2%
108.0799981
 
< 0.1%
2026-02-06T03:47:53.274270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

BOP
Real number (ℝ)

Distinct2388
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.013243118
Minimum-0.96503551
Maximum0.9638981
Zeros6
Zeros (%)0.2%
Negative1172
Negative (%)48.5%
Memory size37.7 KiB
2026-02-06T03:47:55.566493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.96503551
5-th percentile-0.78770334
Q1-0.44421999
median0.023621148
Q30.4727144
95-th percentile0.78423224
Maximum0.9638981
Range1.9289336
Interquartile range (IQR)0.91693439

Descriptive statistics

Standard deviation0.51473621
Coefficient of variation (CV)38.868204
Kurtosis-1.2444146
Mean0.013243118
Median Absolute Deviation (MAD)0.45735569
Skewness-0.041594478
Sum31.98213
Variance0.26495337
MonotonicityNot monotonic
2026-02-06T03:47:55.701673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
06
 
0.2%
0.33333333333
 
0.1%
-0.14159265152
 
0.1%
-0.030303730892
 
0.1%
-0.19780256632
 
0.1%
-0.10937462752
 
0.1%
-0.45333353682
 
0.1%
0.29104428752
 
0.1%
0.252
 
0.1%
-0.067118286512
 
0.1%
Other values (2378)2390
99.0%
ValueCountFrequency (%)
-0.9650355061
< 0.1%
-0.94478521861
< 0.1%
-0.9339266881
< 0.1%
-0.93137279351
< 0.1%
-0.9302962991
< 0.1%
-0.92452661791
< 0.1%
-0.91018091281
< 0.1%
-0.90860502841
< 0.1%
-0.90785994151
< 0.1%
-0.90711989471
< 0.1%
ValueCountFrequency (%)
0.96389809661
< 0.1%
0.9414768051
< 0.1%
0.93382438191
< 0.1%
0.93119197021
< 0.1%
0.93072187411
< 0.1%
0.93051483471
< 0.1%
0.92899465721
< 0.1%
0.92351367241
< 0.1%
0.92118041461
< 0.1%
0.92105566961
< 0.1%

CMO
Numeric time series

High correlation 

Distinct2412
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.42242328
Minimum-84.250049
Maximum70.748687
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:55.853378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-84.250049
5-th percentile-51.041499
Q1-20.783791
median3.1481428
Q322.640865
95-th percentile44.844501
Maximum70.748687
Range154.99874
Interquartile range (IQR)43.424657

Descriptive statistics

Standard deviation29.487346
Coefficient of variation (CV)69.805211
Kurtosis-0.62225993
Mean0.42242328
Median Absolute Deviation (MAD)21.368514
Skewness-0.25526337
Sum1020.1522
Variance869.50358
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value3.560070349 × 10-19
2026-02-06T03:47:56.000422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:56.371858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:57.402537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
26.860883652
 
0.1%
-70.164353122
 
0.1%
32.411962882
 
0.1%
53.127204541
 
< 0.1%
35.582892421
 
< 0.1%
5.6674274311
 
< 0.1%
2.4642254851
 
< 0.1%
-4.1617955431
 
< 0.1%
-11.948523941
 
< 0.1%
-34.217960511
 
< 0.1%
Other values (2402)2402
99.5%
ValueCountFrequency (%)
-84.250049431
< 0.1%
-75.366925531
< 0.1%
-75.295553161
< 0.1%
-74.078478971
< 0.1%
-73.830146791
< 0.1%
-72.838433091
< 0.1%
-72.170229551
< 0.1%
-71.013290811
< 0.1%
-70.164353122
0.1%
-70.014545271
< 0.1%
ValueCountFrequency (%)
70.748686721
< 0.1%
66.854355341
< 0.1%
66.405252121
< 0.1%
66.336344211
< 0.1%
66.257263871
< 0.1%
64.286749231
< 0.1%
62.892409121
< 0.1%
61.903298011
< 0.1%
61.752699621
< 0.1%
61.38212421
< 0.1%
2026-02-06T03:47:56.129422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MFI
Numeric time series

High correlation  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.460473
Minimum6.4260667
Maximum92.781019
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:47:58.127913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.4260667
5-th percentile22.411101
Q137.822884
median49.956301
Q361.153325
95-th percentile75.587922
Maximum92.781019
Range86.354952
Interquartile range (IQR)23.33044

Descriptive statistics

Standard deviation16.107785
Coefficient of variation (CV)0.32566985
Kurtosis-0.49463635
Mean49.460473
Median Absolute Deviation (MAD)11.783052
Skewness-0.061800256
Sum119447.04
Variance259.46074
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.401272676 × 10-13
2026-02-06T03:47:58.261327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:47:58.616271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:47:59.998216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
23.050243921
 
< 0.1%
13.906030551
 
< 0.1%
7.5637786491
 
< 0.1%
7.5885229311
 
< 0.1%
6.4260666671
 
< 0.1%
15.139663481
 
< 0.1%
24.705433381
 
< 0.1%
23.454574781
 
< 0.1%
21.711122561
 
< 0.1%
27.770552011
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
6.4260666671
< 0.1%
7.1776835211
< 0.1%
7.3244300951
< 0.1%
7.5331065311
< 0.1%
7.5637786491
< 0.1%
7.5885229311
< 0.1%
8.4872161821
< 0.1%
9.6835952711
< 0.1%
9.8430221971
< 0.1%
10.052825191
< 0.1%
ValueCountFrequency (%)
92.781019061
< 0.1%
92.269595641
< 0.1%
91.90632521
< 0.1%
90.951770491
< 0.1%
90.717842761
< 0.1%
90.292494381
< 0.1%
88.876316571
< 0.1%
86.414773831
< 0.1%
86.35579031
< 0.1%
85.985264631
< 0.1%
2026-02-06T03:47:58.384770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ROC
Numeric time series

High correlation  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05669029
Minimum-26.188495
Maximum25.066768
Zeros1
Zeros (%)< 0.1%
Memory size37.7 KiB
2026-02-06T03:48:00.783602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-26.188495
5-th percentile-10.613112
Q1-3.6674992
median0.40048675
Q33.8022177
95-th percentile9.9158456
Maximum25.066768
Range51.255263
Interquartile range (IQR)7.4697169

Descriptive statistics

Standard deviation6.2933464
Coefficient of variation (CV)111.01277
Kurtosis0.8219595
Mean0.05669029
Median Absolute Deviation (MAD)3.7058407
Skewness-0.066876169
Sum136.90705
Variance39.606208
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.152644941 × 10-11
2026-02-06T03:48:00.917187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:01.276173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:02.266867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-9.46436971
 
< 0.1%
-8.8129752021
 
< 0.1%
-7.5455141511
 
< 0.1%
-8.187429211
 
< 0.1%
-4.5769226861
 
< 0.1%
-2.2652409041
 
< 0.1%
-0.82452894491
 
< 0.1%
-3.8643564281
 
< 0.1%
-4.4942291831
 
< 0.1%
-4.477813781
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
-26.188495031
< 0.1%
-22.578889051
< 0.1%
-21.101751591
< 0.1%
-20.572355971
< 0.1%
-20.373525491
< 0.1%
-19.514126221
< 0.1%
-19.00912651
< 0.1%
-18.971014711
< 0.1%
-18.691263671
< 0.1%
-18.64567951
< 0.1%
ValueCountFrequency (%)
25.066768121
< 0.1%
23.113101611
< 0.1%
22.320192781
< 0.1%
21.58191981
< 0.1%
21.240516751
< 0.1%
21.187580661
< 0.1%
20.91245651
< 0.1%
20.473583881
< 0.1%
20.393907491
< 0.1%
20.13597441
< 0.1%
2026-02-06T03:48:01.040543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WILLR
Numeric time series

High correlation 

Distinct2411
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-47.472113
Minimum-99.175504
Maximum-0.59403532
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:03.001553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-99.175504
5-th percentile-94.777871
Q1-77.895579
median-44.611522
Q3-18.116945
95-th percentile-4.1300184
Maximum-0.59403532
Range98.581469
Interquartile range (IQR)59.778634

Descriptive statistics

Standard deviation31.227264
Coefficient of variation (CV)-0.65780228
Kurtosis-1.4119858
Mean-47.472113
Median Absolute Deviation (MAD)29.322754
Skewness-0.11888835
Sum-114645.15
Variance975.14204
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.170430659 × 10-16
2026-02-06T03:48:03.142599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:03.531582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:04.868927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-12.3983912
 
0.1%
-56.136097962
 
0.1%
-91.41913092
 
0.1%
-52.152335242
 
0.1%
-7.9754486371
 
< 0.1%
-60.889941881
 
< 0.1%
-69.230718261
 
< 0.1%
-81.122397341
 
< 0.1%
-83.371306521
 
< 0.1%
-94.791678391
 
< 0.1%
Other values (2401)2401
99.4%
ValueCountFrequency (%)
-99.175503981
< 0.1%
-98.931159651
< 0.1%
-98.897642341
< 0.1%
-98.883576841
< 0.1%
-98.823527651
< 0.1%
-98.689967971
< 0.1%
-98.605429141
< 0.1%
-98.548643211
< 0.1%
-98.41090321
< 0.1%
-98.316523981
< 0.1%
ValueCountFrequency (%)
-0.59403532331
< 0.1%
-0.78491751091
< 0.1%
-0.95458505821
< 0.1%
-1.0007645751
< 0.1%
-1.0367634691
< 0.1%
-1.1226342621
< 0.1%
-1.136317661
< 0.1%
-1.1412532131
< 0.1%
-1.2178125211
< 0.1%
-1.2304315471
< 0.1%
2026-02-06T03:48:03.272768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

AD
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2410
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20996973
Minimum-378745.32
Maximum42024321
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:05.598300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-378745.32
5-th percentile3899083.1
Q115616683
median20159890
Q324987341
95-th percentile40232489
Maximum42024321
Range42403067
Interquartile range (IQR)9370658

Descriptive statistics

Standard deviation9916592.4
Coefficient of variation (CV)0.47228677
Kurtosis-0.26365177
Mean20996973
Median Absolute Deviation (MAD)4755675.2
Skewness0.2611822
Sum5.0707689 × 1010
Variance9.8338805 × 1013
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6928202875
2026-02-06T03:48:05.731591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:06.093447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:07.082512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
15436225.062
 
0.1%
18014490.072
 
0.1%
36834620.762
 
0.1%
16976306.492
 
0.1%
24457105.292
 
0.1%
17370862.961
 
< 0.1%
17378193.241
 
< 0.1%
17035905.631
 
< 0.1%
17205434.431
 
< 0.1%
17296048.41
 
< 0.1%
Other values (2400)2400
99.4%
ValueCountFrequency (%)
-378745.32191
< 0.1%
-246463.75031
< 0.1%
-236423.53881
< 0.1%
-192492.54841
< 0.1%
-39361.13461
< 0.1%
13719.767531
< 0.1%
40006.578681
< 0.1%
61869.910741
< 0.1%
98396.925571
< 0.1%
128646.19621
< 0.1%
ValueCountFrequency (%)
42024321.341
< 0.1%
41914665.051
< 0.1%
41863243.41
< 0.1%
41770772.841
< 0.1%
41722133.341
< 0.1%
41703599.71
< 0.1%
41700615.361
< 0.1%
41681480.671
< 0.1%
41673975.351
< 0.1%
41647456.671
< 0.1%
2026-02-06T03:48:05.858026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

OBV
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2410
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3580301.9
Minimum-18013429
Maximum38169761
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:07.814950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-18013429
5-th percentile-11345824
Q1-3273238
median396590
Q33563277.5
95-th percentile31885895
Maximum38169761
Range56183190
Interquartile range (IQR)6836515.5

Descriptive statistics

Standard deviation12566500
Coefficient of variation (CV)3.5098996
Kurtosis0.62612415
Mean3580301.9
Median Absolute Deviation (MAD)3490936
Skewness1.2252818
Sum8.6464291 × 109
Variance1.5791693 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.9917160605
2026-02-06T03:48:07.955519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:08.629045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:09.673685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
287079802
 
0.1%
-18506232
 
0.1%
234401242
 
0.1%
82161542
 
0.1%
-29968542
 
0.1%
-105163741
 
< 0.1%
-98669281
 
< 0.1%
-102688131
 
< 0.1%
-110209871
 
< 0.1%
-108387521
 
< 0.1%
Other values (2400)2400
99.4%
ValueCountFrequency (%)
-180134291
< 0.1%
-179902281
< 0.1%
-174115891
< 0.1%
-173382721
< 0.1%
-172892941
< 0.1%
-172174641
< 0.1%
-171860921
< 0.1%
-169507821
< 0.1%
-169194321
< 0.1%
-167682781
< 0.1%
ValueCountFrequency (%)
381697611
< 0.1%
380408901
< 0.1%
378939521
< 0.1%
378647761
< 0.1%
374514681
< 0.1%
374268891
< 0.1%
373862751
< 0.1%
372055181
< 0.1%
371607411
< 0.1%
371541421
< 0.1%
2026-02-06T03:48:08.080811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

NATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.944752
Minimum1.1250616
Maximum8.4675329
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:10.409448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.1250616
5-th percentile1.5567175
Q12.1657981
median2.6889128
Q33.5184142
95-th percentile5.1811926
Maximum8.4675329
Range7.3424713
Interquartile range (IQR)1.3526161

Descriptive statistics

Standard deviation1.1325748
Coefficient of variation (CV)0.38460787
Kurtosis2.1425499
Mean2.944752
Median Absolute Deviation (MAD)0.61367125
Skewness1.2722736
Sum7111.576
Variance1.2827256
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.00739155243
2026-02-06T03:48:10.556319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:10.929402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:12.236423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2.6048327131
 
< 0.1%
2.6894948471
 
< 0.1%
2.6497204781
 
< 0.1%
2.7199795671
 
< 0.1%
2.7133557951
 
< 0.1%
2.7065870321
 
< 0.1%
2.6624603191
 
< 0.1%
3.0659700391
 
< 0.1%
3.3704430171
 
< 0.1%
3.2601835231
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
1.1250615851
< 0.1%
1.1401127241
< 0.1%
1.1540216811
< 0.1%
1.1650069081
< 0.1%
1.1679474031
< 0.1%
1.1713779551
< 0.1%
1.1721731481
< 0.1%
1.1743342371
< 0.1%
1.1746524081
< 0.1%
1.1756093681
< 0.1%
ValueCountFrequency (%)
8.4675328731
< 0.1%
8.3062247191
< 0.1%
8.2431645741
< 0.1%
8.0736370511
< 0.1%
7.8371079011
< 0.1%
7.7438253541
< 0.1%
7.7040028071
< 0.1%
7.6104261461
< 0.1%
7.6096259521
< 0.1%
7.5619428811
< 0.1%
2026-02-06T03:48:10.686954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ATR
Numeric time series

High correlation  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9914729
Minimum0.95446523
Maximum4.1461225
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:12.984579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.95446523
5-th percentile1.1881208
Q11.5718874
median1.9300417
Q32.2864582
95-th percentile3.1424386
Maximum4.1461225
Range3.1916573
Interquartile range (IQR)0.71457077

Descriptive statistics

Standard deviation0.5778595
Coefficient of variation (CV)0.29016689
Kurtosis0.55009631
Mean1.9914729
Median Absolute Deviation (MAD)0.35812182
Skewness0.82691786
Sum4809.4071
Variance0.3339216
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.01279172203
2026-02-06T03:48:13.132237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:13.502531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:14.494803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.9460704961
 
< 0.1%
1.9813508041
 
< 0.1%
1.9512541441
 
< 0.1%
1.982593091
 
< 0.1%
2.0195507261
 
< 0.1%
2.0902972561
 
< 0.1%
2.0495620431
 
< 0.1%
2.2424504681
 
< 0.1%
2.3994184661
 
< 0.1%
2.3437459151
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
0.95446522891
< 0.1%
0.95716391321
< 0.1%
0.97942401051
< 0.1%
0.98156089081
< 0.1%
0.98168733731
< 0.1%
0.98976842281
< 0.1%
1.0039887571
< 0.1%
1.0095095221
< 0.1%
1.0112891411
< 0.1%
1.0147847021
< 0.1%
ValueCountFrequency (%)
4.146122481
< 0.1%
4.1078280611
< 0.1%
4.061978221
< 0.1%
4.011554781
< 0.1%
3.9354218811
< 0.1%
3.9243009331
< 0.1%
3.8470220071
< 0.1%
3.8421772641
< 0.1%
3.8404953461
< 0.1%
3.8371548961
< 0.1%
2026-02-06T03:48:13.262719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

TRANGE
Real number (ℝ)

High correlation 

Distinct766
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9913871
Minimum0.47999954
Maximum11.129997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:15.179957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.47999954
5-th percentile0.88000107
Q11.3300018
median1.7799988
Q32.4200001
95-th percentile3.7030029
Maximum11.129997
Range10.649998
Interquartile range (IQR)1.0899982

Descriptive statistics

Standard deviation0.9761774
Coefficient of variation (CV)0.49019971
Kurtosis8.1028791
Mean1.9913871
Median Absolute Deviation (MAD)0.51999664
Skewness2.008472
Sum4809.2
Variance0.95292231
MonotonicityNot monotonic
2026-02-06T03:48:15.303038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.518
 
0.7%
1.7517
 
0.7%
1.6100006117
 
0.7%
1.93000030514
 
0.6%
1.52999877914
 
0.6%
114
 
0.6%
1.6399993914
 
0.6%
1.84999847413
 
0.5%
1.45999908413
 
0.5%
1.31999969513
 
0.5%
Other values (756)2268
93.9%
ValueCountFrequency (%)
0.47999954221
< 0.1%
0.48999786381
< 0.1%
0.51
< 0.1%
0.52000045782
0.1%
0.55000305181
< 0.1%
0.56999969481
< 0.1%
0.59000015262
0.1%
0.60000228881
< 0.1%
0.61999893191
< 0.1%
0.62999725341
< 0.1%
ValueCountFrequency (%)
11.129997251
< 0.1%
8.2900009161
< 0.1%
81
< 0.1%
7.7900009161
< 0.1%
7.751
< 0.1%
7.6499938961
< 0.1%
7.3400039671
< 0.1%
7.0999984741
< 0.1%
7.0500030521
< 0.1%
6.7099990841
< 0.1%

TSF
Numeric time series

High correlation  Non stationary  Unique 

Distinct2415
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.995211
Minimum26.556923
Maximum115.04439
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-06T03:48:15.457278image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.556923
5-th percentile41.602099
Q152.060824
median72.979341
Q393.937308
95-th percentile105.21942
Maximum115.04439
Range88.487472
Interquartile range (IQR)41.876484

Descriptive statistics

Standard deviation22.239663
Coefficient of variation (CV)0.30467291
Kurtosis-1.3739523
Mean72.995211
Median Absolute Deviation (MAD)20.939561
Skewness-0.015653405
Sum176283.43
Variance494.60263
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5865554167
2026-02-06T03:48:15.595242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-06T03:48:15.979136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 22.04 seconds
2026-02-06T03:48:17.367259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
73.579011521
 
< 0.1%
72.785494371
 
< 0.1%
72.205494721
 
< 0.1%
71.724395671
 
< 0.1%
71.967911691
 
< 0.1%
72.973956681
 
< 0.1%
73.825496211
 
< 0.1%
73.622199011
 
< 0.1%
72.823408271
 
< 0.1%
72.628462151
 
< 0.1%
Other values (2405)2405
99.6%
ValueCountFrequency (%)
26.556922891
< 0.1%
26.675714161
< 0.1%
27.112527871
< 0.1%
27.386043931
< 0.1%
27.508570951
< 0.1%
27.530769471
< 0.1%
27.770109641
< 0.1%
27.795824431
< 0.1%
28.042306981
< 0.1%
28.196264331
< 0.1%
ValueCountFrequency (%)
115.04439461
< 0.1%
114.43120851
< 0.1%
114.18791261
< 0.1%
113.29384511
< 0.1%
112.67208841
< 0.1%
111.81538471
< 0.1%
111.36846191
< 0.1%
111.11615331
< 0.1%
111.03461661
< 0.1%
110.76626391
< 0.1%
2026-02-06T03:48:15.722586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-06T03:47:38.191796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.398485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.652347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.898765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.460432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.921643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.214032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.540467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.058023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.510673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.155803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.469810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.843279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.174989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.605551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.074058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.834401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.260234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.468535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.720030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.965869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.541127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.997024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.288804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.626283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.141283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.583979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.228904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.546914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.917011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.253474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.691379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.160315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.915050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.330266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.537811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.788222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.032599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.620262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.071691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.356738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.710151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.221309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.657759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.303985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.622742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.991640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.335611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.775657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.246711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.992381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.398391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.604969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.854914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.100144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.699237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.147533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.426687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.796054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.306278image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.732839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.377604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.700462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.064065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.413244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.856926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.629878image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.067988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.479578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.686347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.933737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.178737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.789126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.229213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.507604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.892517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.397758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.824343image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.461581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.788790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.151680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.504689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.948447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.719905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.154693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.549721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.754089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.001965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.247531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.867543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.300196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.582144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.977936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.481769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.899950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.535439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.866152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.225019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.583966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.030429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.798553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.231443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.619632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.822248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.069608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.315758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.947628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.372031image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.658212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.062295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.563268image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.978541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.609622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.942010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.298732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.664358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.111016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.876974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.307165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.705512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.906764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.154677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.399689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.041698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.459216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.749474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.158263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.659098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.070107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.695807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.034228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.387022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.756387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.206578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:35.972422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.398605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.785013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:15.985063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.232208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.477957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.132801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.547318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.836706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.251894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.745475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.157038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.778016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.118675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.469417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.845397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.295791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.061462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.483674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.853830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.054619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.303112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.545178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.214048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.615495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.910714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.337441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.824281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.553270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.848964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.194921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.545507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.923472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.376458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.141912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.557947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.928099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.126296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.374882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.617533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.297023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.689099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.988883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.424299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.907790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.626949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.921985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.278527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.626635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.003460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.457621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.222138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.640220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:39.003552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.201302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.448115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.690503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.384328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.763533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.072489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.515010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:25.991806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.703452image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.998307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.356232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.706081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.088576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.544027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.309719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.720716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:39.078781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.274932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.522064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.763960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.467696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.835582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.151482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.602822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.075804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.776348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.072575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.435061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.781266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.169202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.625311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.388766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.798782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:39.156482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.351619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.603080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.839881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.558313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.913478image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.238927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.693993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.163673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.855844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.154326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.517677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.860100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.254725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.718657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.476249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.879471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:39.235259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.431302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.682020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.916620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.646335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:21.990592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.316919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.788195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.254897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:27.934206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.236220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.603069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:31.942212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.346931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.808917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.569416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:37.962013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:39.313768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.509970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.759292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:18.994221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.738200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.070223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.394586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.880933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.344096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.013575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.320883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.685920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.023010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.437001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.900499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.661751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.042933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:39.387030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:16.583572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:17.831198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:19.069393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:20.832370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:22.145048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:23.470484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:24.972121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:26.431231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:28.087365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:29.396281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:30.767911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:32.101778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:33.520906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:34.989245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:36.749738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-06T03:47:38.117912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-06T03:48:18.052547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ADATRBOPCMOEMAKAMAMAMFIMidPriceNATROBVROCTRANGETSFWILLRWMAclose
AD1.000-0.4730.013-0.010-0.123-0.119-0.124-0.003-0.122-0.2470.644-0.035-0.297-0.131-0.039-0.124-0.127
ATR-0.4731.000-0.024-0.1500.2830.2810.281-0.0940.2810.498-0.268-0.0600.6540.272-0.0760.2800.277
BOP0.013-0.0241.0000.3880.0080.0030.0030.1620.004-0.0670.0740.291-0.0760.0170.4700.0090.059
CMO-0.010-0.1500.3881.0000.0560.0380.0450.7710.042-0.2400.1610.865-0.2090.1320.9290.0740.140
EMA-0.1230.2830.0080.0561.0000.9981.0000.0330.999-0.6400.3600.0060.1820.9940.0381.0000.995
KAMA-0.1190.2810.0030.0380.9981.0000.9980.0220.998-0.6400.361-0.0110.1840.9910.0180.9980.992
MA-0.1240.2810.0030.0451.0000.9981.0000.0280.999-0.6390.358-0.0060.1830.9930.0250.9990.992
MFI-0.003-0.0940.1620.7710.0330.0220.0281.0000.023-0.1670.1440.720-0.1300.1090.7260.0510.092
MidPrice-0.1220.2810.0040.0420.9990.9980.9990.0231.000-0.6400.358-0.0140.1820.9920.0190.9980.992
NATR-0.2470.498-0.067-0.240-0.640-0.640-0.639-0.167-0.6401.000-0.543-0.1280.348-0.649-0.168-0.643-0.648
OBV0.644-0.2680.0740.1610.3600.3610.3580.1440.358-0.5431.0000.090-0.1760.3620.1350.3610.365
ROC-0.035-0.0600.2910.8650.006-0.011-0.0060.720-0.014-0.1280.0901.000-0.1260.0880.8720.0240.084
TRANGE-0.2970.654-0.076-0.2090.1820.1840.183-0.1300.1820.348-0.176-0.1261.0000.170-0.1620.1790.168
TSF-0.1310.2720.0170.1320.9940.9910.9930.1090.992-0.6490.3620.0880.1701.0000.1090.9970.996
WILLR-0.039-0.0760.4700.9290.0380.0180.0250.7260.019-0.1680.1350.872-0.1620.1091.0000.0530.123
WMA-0.1240.2800.0090.0741.0000.9980.9990.0510.998-0.6430.3610.0240.1790.9970.0531.0000.996
close-0.1270.2770.0590.1400.9950.9920.9920.0920.992-0.6480.3650.0840.1680.9960.1230.9961.000

Missing values

2026-02-06T03:47:39.513283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-06T03:47:39.650942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Datecloserepaired?MAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2010-01-262010-01-2674.709999False77.50600177.38547475.94990576.44363778.079998-0.363057-50.44267423.050244-9.464370-91.21421998396.925575-1320283.02.6048331.9460701.57000073.579012
2010-01-272010-01-2773.669998False76.79400076.70993375.44845875.74618276.660000-0.418035-55.95138213.906031-8.812975-90.97347740006.578683-1676462.02.6894951.9813512.43999572.785494
2010-01-282010-01-2873.639999False76.19300076.15176375.08895775.17272776.505001-0.070513-56.1077537.563779-7.545514-91.23895313719.767531-1969373.02.6497201.9512541.55999872.205495
2010-01-292010-01-2972.889999False75.54300075.55871574.63031374.57218275.869999-0.418410-60.0476287.588523-8.187429-96.006951-192492.548422-2304643.02.7199801.9825932.38999971.724396
2010-02-012010-02-0174.430000False75.18600075.35349474.61497374.36981875.7900010.636002-32.8425986.426067-4.576923-79.818357-39361.134604-2027232.02.7133562.0195512.50000071.967912
2010-02-022010-02-0277.230003False75.00700175.69467874.67781274.74145575.7300000.7607971.11432715.139663-2.265241-41.747521283101.563080-1660963.02.7065872.0902973.01000272.973957
2010-02-032010-02-0376.980003False74.94300175.92837374.70098775.10018375.395000-0.006575-1.38640324.705433-0.824529-42.622915128646.196177-2052257.02.6624602.0495621.52000473.825496
2010-02-042010-02-0473.139999False74.64900175.42139674.63850474.77236475.230000-0.831578-30.65578223.454575-3.864356-89.550054-236423.538763-2576149.03.0659702.2424504.75000073.622199
2010-02-052010-02-0571.190002False74.31400174.65205274.48017674.14345673.770000-0.416666-40.60298721.711123-4.494229-82.487024-378745.321896-3172291.03.3704432.3994184.44000272.823408
2010-02-082010-02-0871.889999False73.97700074.14986174.36001173.70272873.770000-0.179013-32.99373927.770552-4.477814-74.921304-246463.750290-2826653.03.2601842.3437461.62000372.628462
Datecloserepaired?MAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2019-08-192019-08-1956.209999False54.45700055.15684656.12510255.03600053.9950010.7961787.19337849.2356432.779302-31.4457933.955044e+0737205518.03.6209262.0353231.57000054.870768
2019-08-202019-08-2056.340000False54.72800055.37196556.13282455.37836353.9950010.1818198.24046749.3474265.053140-22.0883703.994999e+0737864776.03.5218821.9842281.32000055.967142
2019-08-212019-08-2155.680000False55.18700055.42797256.08875855.55145454.705000-0.2341761.76379158.2981108.984146-25.7554063.936181e+0737160741.03.5117721.9553551.58000256.134725
2019-08-222019-08-2255.349998False55.46800055.41379556.04869355.58109054.920000-0.366460-1.51024550.6616785.348301-30.5036333.912631e+0736539168.03.4881421.9306871.61000156.451648
2019-08-232019-08-2354.169998False55.43499955.18765056.03481455.34509055.355001-0.500001-12.67278750.799555-0.605508-47.4820533.895530e+0735732017.03.6207341.9613522.35999756.271098
2019-08-262019-08-2653.639999False55.30599954.90625955.98277155.01872755.2150000.169565-17.34773850.832291-2.348445-55.1079343.867779e+0735052995.03.7016051.9855412.29999955.769889
2019-08-272019-08-2754.930000False55.08900054.91057555.93254554.95036355.0450000.576355-2.50705760.349765-3.800347-45.9312793.881004e+0735649619.03.6269581.9922882.08000255.190329
2019-08-282019-08-2855.779999False55.14399955.06865255.93073755.07599955.0450000.0496456.17977160.3204360.995834-33.1372883.855668e+0736323667.03.5496271.9799821.82000054.981977
2019-08-292019-08-2956.709999False55.36799955.36707955.97602155.36072755.0450000.56849214.94255860.0061934.112351-16.8514813.903190e+0736954427.03.4259211.9428401.45999955.277142
2019-08-302019-08-3055.099998False55.39099955.31851955.97039155.31199955.045000-0.705070-2.56279952.0694310.419172-52.5499253.868267e+0736246159.03.5554741.9590662.17000255.115054